Predicting 30-Day Pneumonia Readmissions Using Electronic Health Record Data.

ABSTRACT:

Background

Readmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction.

Objective

To develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay").

Design

Observational cohort study using stepwise-backward selection and cross-validation.

Subjects

Consecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010.

Measures

All-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals.

Results

Of 1463 patients, 13.6% were readmitted. The first-day pneumonia-specif

SUBMITTER: Makam AN 

PROVIDER: S-EPMC6296251 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature